Estimasi Risiko VaR-CVaR pada Pembentukan Portofolio Menggunakan Metode Single-Multiple Index Model dan Hierarchical Equal Risk Contribution

Marshandah, Gharizah Meuthia (2025) Estimasi Risiko VaR-CVaR pada Pembentukan Portofolio Menggunakan Metode Single-Multiple Index Model dan Hierarchical Equal Risk Contribution. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Berinvestasi pada saham akan sangat menguntungkan bagi seorang investor, tetapi juga mempunyai risiko karena harga saham dapat mengalami fluktuasi. Sebelum membentuk sebuah portofolio investasi, investor harus menyeleksi saham penyusun sehingga dapat memberikan hasil yang optimal. Metode yang dapat digunakan untuk membentuk portofolio optimal yaitu Single Index Model, Multiple Index Model dan Hierarchical Equal Risk Contribution. Single Index Model menyederhanakan perhitungan dengan membagi risiko menjadi dua, yaitu risiko pasar dan risiko unik. Multiple Index Model mampu mempertimbangkan lebih dari satu faktor yang memengaruhi return saham, tidak hanya indeks pasar. Sementara itu, metode HERC menentukan bobot berdasarkan tingkat risiko dalam struktur hierarki atau dendogram yang terbentuk. Objek penelitian yang digunakan dalam penelitian adalah closing price saham dari 10 perusahaan pada sektor perbankan yang tergabung dalam Bursa Efek Indonesia (BEI), Indeks pasar (IHSG), dan indeks industrial (TWII, DJIA, dan NI225) dengan periode Januari 2022 – Januari 2025. Metode Single Index Model (SIM) menghasilkan portofolio dengan 7 saham dengan nilai expected return sebesar 0,035452. Sementara itu, metode Multiple Index Model (MIM) menghasilkan portofolio dengan 6 saham dengan expected return sebesar 0,000448. Adapun metode Hierarchical Equal Risk Contribution (HERC) menghasilkan portofolio dengan 10 saham dengan expected return sebesar 0,000276. Setelah mendapatkan portofolio optimal, dibutuhkan perhitungan risiko maksimum yang akan dihadapi dengan mengestimasi nilai VaR dan CVaR. Hasil estimasi nilai VaR dan CVaR menunjukkan bahwa HERC lebih unggul dalam meminimalkan risiko dibandingkan SIM dan MIM pada seluruh tingkat kepercayaan. Nilai yang dihasilkan pada tingkat kepercayaan 90%, 95%, dan 99% dengan VaR sebesar 0,9092%, 1,2287%, dan 1,9202%, serta CVaR sebesar 1,3637%, 1,6714%, dan 2,3211%.
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Investing in stocks will be very profitable for an investor, but it also has risks because the stock price index can fluctuate. Before forming an investment portfolio, investors must select the constituent stocks so that they can provide optimal results. The methods that can be used to form an optimal portfolio are the Single Index Model, Multiple Index Model and Hierarchical Equal Risk Contribution. The Single Index Model simplifies calculations by dividing risk into two components: market risk and unique risk. The Multiple Index Model considers more than one factor affecting stock returns, not just the market index. Meanwhile, the HERC method determines portfolio weights based on risk levels derived from a hierarchical structure or dendrogram. The research objects used in the study are the closing stock prices of 10 companies in the banking sector listed on the Indonesia Stock Exchange (IDX), the market index (IHSG), and the industrial index (TWII, DJIA, and NI225) for the period January 2022 - January 2025. The Single Index Model (SIM) method produces a portfolio of 7 stocks with an expected return value of 0.035452. Meanwhile, the Multiple Index Model (MIM) method produces a portfolio of 6 stocks with an expected return of 0.000448. The Hierarchical Equal Risk Contribution (HERC) method produces a portfolio of 10 stocks with an expected return of 0.000276. After obtaining the optimal portfolio, a calculation of the maximum risk that will be faced is needed by estimating the VaR and CVaR values. The results of the estimated VaR and CVaR values show that HERC is superior in minimizing risk compared to SIM and MIM at all levels of confidence. The values generated at the 90%, 95%, and 99% confidence levels with VaR of 0.9092%, 1.2287%, and 1.9202%, and CVaR of 1.3637%, 1.6714%, and 2.3211%.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	CVaR, Hierarchical Equal Risk Contribution, Single Index Model, Multiple Index Model, VaR ============================================================ CVaR, Hierarchical Equal Risk Contribution, Single Index Model, Multiple Index Model, VaR
Subjects:	Q Science > QA Mathematics > QA273.6 Weibull distribution. Logistic distribution. Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression Q Science > QA Mathematics > QA278.55 Cluster analysis
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Gharizah Meuthia Marshandah
Date Deposited:	24 Jul 2025 08:09
Last Modified:	24 Jul 2025 08:09
URI:	http://repository.its.ac.id/id/eprint/121357

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